Anteater: Interactive Visualization of Program Execution Values in Context

Abstract

Fig. 1. A programmer investigates a bug in their code. One common practice, shown in the top row, is to instrument the program manually to collect suspicious variables (in this case x), and print out their values. Manual instrumentation, however, is itself error-prone and leaves the programmer responsible for sifting through values. Another common practice, shown in the second row, is to use a debugger to stop the execution of the program automatically and view each assignment of x individually. However, breakpoint-debugging tends to provide only a narrow, one-at-a-time view of the values. Anteater, shown in the bottom row, automatically instruments the code to track variables along with the context of their execution structure. It presents the programmer with interactive visualizations that give a global view of values, which allow for easy detection of erroneous values as well as interactions to narrow down the visualizations to inspect specific values. We provide a demo of Anteater in action as supplemental material.

A Dataflow Analysis for Comparing and Reordering Predicate Arguments

“…Let us now consider that our program is also constituted of a moded version of the concat/3 predicate introduced in Section 1: The predicate calls in the example above being recursive calls, we introduce the following example to illustrate the case where a predicate makes calls to other predicates. The analysis finds the following final interaction set for dapp: (5),ψ ⊥ (4),ψ a (11),⇒ cons (8),⇐ cons (10),ψ ⊥ (9),ψ a (12)} L4, L2 {:=(2),ψ ⊥ (4),⇐ cons (5),ψ a (11),⇒ cons (8),⇐ cons (10),ψ ⊥ (9),ψ a (12)} L4, L3 {:=(7),ψ ⊥ (9),⇐ cons (10),ψ a (12)…”

PyTracer: Automatically profiling numerical instabilities in Python

“…Existing tools for tracing Python code focus on performance profiling for time (cProfile) or memory consumption (memprofile). Anteater [12] is a Python tracer tool to debug Python applications. It performs source transformations at the AST level but only deals with native numeric Python types.…”